Multi-label classification aims at assigning more than one label to each instance. Many real-world multi-label classification tasks are high dimensional, leading to reduced performance of traditional classifiers. Feature selection is a common approach to tackle this issue by choosing prominent features. Multi-label feature selection is an NP-hard approach, and so far, some swarm intelligence-based strategies and have been proposed to find a near optimal solution within a reasonable time. In this paper, a hybrid intelligence algorithm based on the binary algorithm of particle swarm optimization and a novel local search strategy has been proposed to select a set of prominent features. To this aim, features are divided into two categories based on the extension rate and the relationship between the output and the local search strategy to increase the convergence speed. The first group features have more similarity to class and less similarity to other features, and the second is redundant and less relevant features. Accordingly, a local operator is added to the particle swarm optimization algorithm to reduce redundant features and keep relevant ones among each solution. The aim of this operator leads to enhance the convergence speed of the proposed algorithm compared to other algorithms presented in this field. Evaluation of the proposed solution and the proposed statistical test shows that the proposed approach improves different classification criteria of multi-label classification and outperforms other methods in most cases. Also in cases where achieving higher accuracy is more important than time, it is more appropriate to use this method.

Objective: The purpose of this study was to conduct a systematic analytical study of the use of artificial intelligence in higher education from 2016 to 2022.Methods: In this research, the PRISMA method, which is a systematic meta-analysis method based on evidence, was used. 138 articles written about using artificial intelligence in the higher education system were examined and the resulting data were extracted and analyzed using prior and contextual codingResults: The findings of this study show that in 2021 and 2022, the number of publications related to this topic increased nearly 3 times compared to the previous years, with a rapid increase in the number of educational publications on artificial intelligence in higher education and new procedures have emerged.Conclusion: Research has been conducted on six of the world's seven continents, and this trend has shifted from the United States to China, which now leads in the number of publications in this field. Also, the absence of researchers from different educational groups, the gaps in the literature of this field, and the explanation of how artificial intelligence is used in higher education are other research results.

Background and aim: Ethics is an inseparable part of nursing duties body and one of the most important factors influencing human behavior. In fact, ethics can be considered as one of the main factors in promoting respect of patient' rights. Purpose: The purpose of this study was to investigate the ethical intelligence of nurses working in general and intensive care units in Tehran's selected military hospital. Methods: This descriptive-analytical study was performed from July until November 2018. The study was conducted on 120 out of 1, 200 nurses working in the hospital who were selected based on the Morgan sample size table and allocated to the general and intensive care units, 40 of which were in the intensive care unit and 80 in the internal and surgical units. Ethical intelligence of the samples was measured using the Lenik and Kiel moral intelligence questionnaire and then analyzed using SPSS 20 software. Results: The inclusion criteria were at least one year of job experience, at least a bachelor's degree in nursing and aged 22 to 50 years. The samples consisted of 56 females and 64 males, of which 107 were married and 13 single, 12 had a master's degree and 108 bachelor's degree. The mean and standard deviation of nurses' moral intelligence was 75. 25 (SD=8. 47) and in general wards was 73. 26 (SD=9. 87) and in intensive care unit nurses was 77. 25 (SD=7. 07). The highest level among the four criteria of nurses' moral intelligence was honesty in the general and intensive care units with a mean of 79. 62 (SD=11. 22) which in the general unit 79. 00 (SD=10. 32) and in intensive care unit 80. 25 (SD=12. 12). The results showed that 77. 5% of nurses were in good and higher level of moral intelligence. Conclusion: The results indicate the importance and place of ethical teaching in nursing. The nurse's attitude towards the patient, herself and her job can promote this profession. Therefore, today acquiring ethical knowledge and the ability to cultivate nurses' moral intelligence is one of the essentials in this profession. It is recommended to provide appropriate ethics training for nurses in the form of in-service courses. due to the difference in the nurses moral intelligence in the general and intensive care units, which indicates hospital managers pay more attention to the intensive care units, so managers need to have the same sensitivity and attention to general units as to intensive care units.

Artificial intelligence futurology, based on divine laws (using James Detour's analytical model).According to the Quranic teachings, the divine laws (such as the Isthilaf law) rule the world. On the other hand, with the current rapid growth, artificial intelligence may enter the technical era. Now, with the premise of the possibility of singularity, if it is realized, can artificial intelligence prevent the flow of divine laws, the realization of a desirable and honorable society? Finally, after planning, explaining and categorizing the possible scenarios for the future of artificial intelligence based on the analytical method of James Detour , their feasibility and proportionality based on various divine laws, while rejecting worrisome scenarios, it was concluded that according to conditional and absolute competitive traditions and based on the evolutionary movement of societies and history, although it is possible that the growth of artificial intelligence will cause harm and concerns for Man should follow; But Saleh's succession is certain and the growth of technology will not prevent its flow. In this research, information was collected by library method and their processing was done by descriptive-analytical method.

Background and Objective: Physical and mental health are shown to have correlations based upon which parameters including weight, height and feeding behaviors may affect intellectual functions. The present study investigates the correlations between feeding behavior induced changes in anthropometric parameters and the different components of intelligence in children living in two socio-economically different districts in Tehran-Iran. methods: It was a descriptive-analytical study. Food consumption data was collected through questionnaires and interviews and normalized using USDA database to derive energy intakes. Different aspects of intelligence were assessed using Shutte scale and Raven's standard metrics for IQ. The subjects of this research includes 184 students from district 1 and 19 of Tehran city who were selected by simple random sampling method and were assesd for anthropometric during the follow ups in the hospital clinic. Results: There was a weak significant negative correlation (r=-0. 134) between weight and also weight for age (r=-0. 244) and emotional intelligence but not between BMI and IQ or emotional intelligence. Height negatively correlated with intelligence quotient (IQ) (r=-0. 144). Students living in District 19 showed more intake of energy than D. 1 while male students received more energy than females in the later area. In both areas the amount of energy supply was more than needed most of which was gained through intake of carbohydrates and fat. Conclusion: Both districts were significantly different in feeding behaviors and economic levels. Unhealthy feeding behaviors were more prominent in District 19 and overweight might have significant impacts on mental health and intelligence. It is a descriptive-analytical study based on its objectives. Food consumption data was collected through questionnaires and interviews and normalized using USDA database to derive energy intakes. Different aspects of intelligence were assessed using Shutte scale and Raven's standard metrics for IQ. The subjects of this research includes 184 students from district 1 and 19 of Tehran city who were selected by simple random sampling method. There was a weak significant negative correlation (r=-0. 134) between weight and also weight for age (r=-0. 244) and emotional intelligence but not between BMI and IQ or emotional intelligence. Height negatively correlated with intelligence quotient (IQ) (r=-0. 144). Students living in District 19 showed more intake of energy than D. 1 while male students received more energy than females in the later area. In both areas the amount of energy supply was more than needed most of which was gained through intake of carbohydrates and fat. Both districts were significantly different in feeding behaviors and economic levels. Unhealthy feeding behaviors were more prominent in District 19 and overweight might have significant impacts on mental health and intelligence.

Background and Aim: Large amounts of hospital costs are not reimbursed annually by health insurance as deductions. Therefore, reducing deductions is very important for the hospital. In the study of design and implementation of analytical dashboard of insurance deductions based on medical intelligence business, to improve financial management with the aim of focusing on assessing the level of satisfaction and its applicability has been done. Materials and Methods: To design the questionnaire, first 27 questions were prepared through library studies and interviews with members of the hospital board of directors, and the validity and consistency of its items were determined through content validity and Cronbach’, s alpha coefficient. Data were analyzed in SPSS software and the results were used to design and implement the dashboard. Results: The study is of development-applied type. In the first phase, to determine Content Validity Ratio CVI (Content Validity Index), and CVR (Content Validity Ratio) a researcher-made questionnaire was provided to 20 experts. In the second phase, by building a data warehouse in SQL (Structured Query Language), the information of the tables related to the deductions of the hospital HIS system was transferred to it and the operational information of the organization was extracted and converted into DW format and the map information was tested. OLAP (Online analytical Processing) services were then loaded on the created analytics database. In the last step, Power BI tool was selected and used to create business intelligence mechanisms, display and visualize information. In the third phase, using the QUIS (Questionnaire for User Interface Satisfaction) standard questionnaire, the level of satisfaction and usability of the dashboard was evaluated by 15 experts. Conclusion: In this study, two questionnaires were used. CVR was measured in all items of the first questionnaire, more than 0. 50 and CVI was measured in the upper areas of 0. 90 and Cronbach’, s alpha coefficient was obtained between 0. 8 and 0. 9, which indicated a good level. The second questionnaire was to evaluate the level of satisfaction and usability of the dashboard that the average of the total evaluation based on the indicators of the QUIS questionnaire is equal to 85. 40. Therefore, the level of satisfaction and usability of the dashboard was “, very good”,for the evaluators.

The present study was conducted with the aim of the impact of Sternberg's three-dimensional intelligence on the level of marital compatibility. The descriptive research method was correlation type. The statistical population of the research was all couples in Tehran in 2022. According to Morgan's table, the research sample was 384 married men and women. The sampling method was chosen voluntarily. Research tools were Graham B. Spanier's Marital Compatibility Questionnaire and Grigorenko and Sternberg's Successful intelligence Questionnaire. The data analysis method was also determined by regression analysis. The findings of the research showed that three analytical intelligences, creative intelligences, and practical intelligences from Sternberg's point of view can have an impact on the compatibility of couples. Meanwhile, the influence of creative intelligence is greater than other intelligences. It can be concluded that intelligence as an important factor can play an important role in the marital compatibility of couples.

The aim of this research was investigate the role of analytical intelligence in career interests with mediated by academic achievement of specific subjects in students. This is a descriptive-analytical study of structural equation modeling. The population included all high school students at the mathematical, experimental and humanistic fields of Urmia. Totally 370 students were selected by cluster random sampling method and completed the analytical intelligence scale and career interests’ scale. The mean of specific lessons of mathematical, experimental and humanistic considered as an indicator of academic achievement. The data were analyzed by structural equation modeling. The findings showed analytical intelligence with mediated academic achievement at the mathematic, physics, chemistry and biology lessons has direct and indirect positive and significant effect on all aspect of vocational interests. In addition the analytical intelligence with mediated academic achievement at the islamic studies, arabic, english and persian literature lessons has an indirect negative and significant effect on all aspect of vocational interests. The findings emphasize the importance of the impact of analytical intelligence and academic achievement at the specific lessons on career interests of high school students.